Viswanathan K's Thoughts

Neural networks. Deep learning. This is the “how” behind what we see as AI (artificial intelligence) around us today, from Alexa’s voice recognition to Google’s image search to your smartphone’s ability to unlock based on your face. While these algorithms are very powerful indeed, they are also mysterious…   “Mysterious”? What does that even mean? Simply put, we don’t understand how they conclude what they conclude. It’s not as if someone wrote specific software instructions on how to recognize a dog. Rather, a huge set of data is provided as input with tags like “dog” and “not dog”. The system goes over the data and self-discovers which patterns correspond to a dog. Remember that old joke on computers as GIGO (Garbage In, Garbage Out)? That joke was based on instructions we keyed into a computer (type the wrong instruction, you get the wrong result). With AI, GIGO now means something else – feed it the wrong data and/or wrong tags as input, and the patterns the system learn...

The preamble to the constitution. That’s the topic of Aakash Singh Rathore’s Ambedkar’s Preamble . Not the entire constitution, just the preamble. Why a book on just the preamble? The author explains: “The ideas and principles behind a clause can be more important than the mere mechanics of the clause itself.”   It starts with something we don’t even notice this: “WE, THE PEOPLE OF INDIA… IN OUR CONSTITUENT ASSEMBLY this twenty-sixth day of November, 1949, do HEREBY ADOPT, ENACT AND GIVE TO OURSELVES THIS CONSTITUTION.” Not 26 January, 1950 (our Republic Day). Instead, 26 November 1949. And if it was ready on that earlier day, why did our Republic Day have to be later?   Therein lies a tale. In 1929, the Congress’ National Session made a call for complete independence. A while later, Gandhi published an article on 26 January 1930 saying India would settle for nothing less than “complete independence”. It was as a callback to that Gandhian demand that the coun...

The last pillar of India’s DPI (Digital Public Infrastructure) is privacy . We take that to mean control over who knows what, whether that info can be shared with others, for how long it can be retained etc. Yes, privacy is all those things.   But India’s DEPA takes it a lot further, explains Rahul Matthan in The Third Way . It actively seeks to ensure portability (Unlike those private corporations which deliberately have data is in non-standard formats to prevent interoperability). Even better, DEPA has “been designed to support requests for specific items of data ”. An example helps. When we apply for say a visa, the issuing country really only wants to know if we earn enough (salary month on month). But the bank statement exposes every transaction. The DEPA framework allows you to select only salary credits be shown and everything else blacked out.   The next issue with privacy is consent , i.e., explicit permission of the individual. In theory, the solution lie...

Eugene Wei makes some interesting points on the topic of copying the work of others. Quite often, it isn’t just copying – rather, what’s being “copied” serves as the inspiration: “Isn't this how innovation happens? We stand on the shoulder of giants and all that? Good artists copy, great artists steal?” In case you’re wondering, that last line (on what artists do) is by Steve Jobs.   If a work of literature (or parts of it) is copied, we rightly call it plagiarism. But interestingly, in the world of business, an old idea can be copied and tried again (as long as it doesn’t violate copyrights, patents and trademarks). How’s that? In layman English, we say an idea was ahead of its time. In business parlance, it’s called “product-market fit” mismatch – a product, like an idea, that is too ahead of its time won’t succeed. Which is why the same product/idea relaunched later might succeed: “One day, the conditions are finally right, and an idea that has failed ten times before...

In Range , David Epstein argues that the “ability to integrate broadly” is our greatest strength. Which is the “exact opposite of narrow specialization”. If we narrowly know only one area very well, we tend to look and find only the “same old patterns”. But: “In the wicked world, with ill-defined challenges and few rigid rules, range can be a life hack.”   Most problems in a field can be solved by specialists in that field. That’s to be expected. But when experts in a field get stuck, quite often we see outsiders with a broad range of knowledge of multiple fields (even if they’re not specialists in most of those fields) finding solutions. Why/how? “The outside view probes for deep structural similarities to the current problem in different ones. The outside view is deeply counterintuitive because it requires a decision maker to ignore unique surface features of the current project, on which they are the expert, and instead look outside for structurally similar analogies.” ...

When we think of online retail in India, we think of Amazon and Flipkart. Which is why I found this article by Manish Singh so informative: “ Flipkart and Amazon’s displacement is coming from two directions simultaneously.”   The first of those are the urban “instant delivery” firms. Think Blinkit, Swiggy’s Instamart and Zepto. The second one are e-commerce sites aimed at the smaller cities and towns. “ Amazon and Flipkart now find themselves squeezed between two models they cannot easily replicate because their expensive infrastructure, designed for catalogue breadth and next-day delivery, proves ill-suited for either 10-minute deliveries in dense urban areas or ultra-low-price commerce in India’s interior.”   I won’t spend much time on the instant delivery firms since we (in urban centers) are very familiar with their speed and convenience.   I will talk more on the e-commerce sites for smaller cities and towns. Meesho is what few of us have ever used...